open-llm-leaderboard-old/details_unit-mesh__autodev-deepseek-6.7b-finetunes-poc

该数据集是在模型 unit-mesh/autodev-deepseek-6.7b-finetunes-poc 在 Open LLM Leaderboard 上的评估运行期间自动创建的。数据集由 63 个配置组成，每个配置对应一个评估任务。数据集是从 1 次运行中创建的，每次运行作为每个配置中的一个特定分割，分割名称使用运行的时间戳。train 分割始终指向最新结果。一个额外的配置 results 存储了运行的所有聚合结果，用于计算和显示 Open LLM Leaderboard 上的聚合指标。README 还提供了如何使用 Python 代码加载运行中的详细信息的示例，并包含了特定运行的最新结果。

原始信息汇总

数据集概述

数据集摘要

该数据集是在对模型 unit-mesh/autodev-deepseek-6.7b-finetunes-poc 进行评估运行期间自动创建的，评估运行在 Open LLM Leaderboard 上进行。

数据集组成

• 数据集包含 63 个配置，每个配置对应一个评估任务。
• 数据集从 1 次运行中创建，每次运行可以在每个配置中找到特定的拆分，拆分名称使用运行的时间戳。
• "train" 拆分始终指向最新的结果。
• 额外的配置 "results" 存储所有运行的聚合结果，用于计算和显示 Open LLM Leaderboard 上的聚合指标。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_unit-mesh__autodev-deepseek-6.7b-finetunes-poc", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-15T10:40:27.582189 运行的最新结果：

python { "all": { "acc": 0.3755993742028831, "acc_stderr": 0.03423029641090857, "acc_norm": 0.3777627808573008, "acc_norm_stderr": 0.03497427995401455, "mc1": 0.29008567931456547, "mc1_stderr": 0.01588623687420952, "mc2": 0.4411102243659991, "mc2_stderr": 0.01482842849226169 }, "harness|arc:challenge|25": { "acc": 0.33276450511945393, "acc_stderr": 0.013769863046192307, "acc_norm": 0.35409556313993173, "acc_norm_stderr": 0.013975454122756555 }, "harness|hellaswag|10": { "acc": 0.40669189404501094, "acc_stderr": 0.004902125388002211, "acc_norm": 0.5240987851025692, "acc_norm_stderr": 0.004983982396187372 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4074074074074074, "acc_stderr": 0.042446332383532286, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.042446332383532286 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.3355263157894737, "acc_stderr": 0.03842498559395269, "acc_norm": 0.3355263157894737, "acc_norm_stderr": 0.03842498559395269 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.3886792452830189, "acc_stderr": 0.03000048544867599, "acc_norm": 0.3886792452830189, "acc_norm_stderr": 0.03000048544867599 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3402777777777778, "acc_stderr": 0.03962135573486219, "acc_norm": 0.3402777777777778, "acc_norm_stderr": 0.03962135573486219 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3236994219653179, "acc_stderr": 0.0356760379963917, "acc_norm": 0.3236994219653179, "acc_norm_stderr": 0.0356760379963917 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.18627450980392157, "acc_stderr": 0.038739587141493524, "acc_norm": 0.18627450980392157, "acc_norm_stderr": 0.038739587141493524 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.33617021276595743, "acc_stderr": 0.030881618520676942, "acc_norm": 0.33617021276595743, "acc_norm_stderr": 0.030881618520676942 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.04266339443159394, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.04266339443159394 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4896551724137931, "acc_stderr": 0.04165774775728763, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.04165774775728763 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.28835978835978837, "acc_stderr": 0.023330654054535892, "acc_norm": 0.28835978835978837, "acc_norm_stderr": 0.023330654054535892 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30158730158730157, "acc_stderr": 0.041049472699033945, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.041049472699033945 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4064516129032258, "acc_stderr": 0.027941727346256308, "acc_norm": 0.4064516129032258, "acc_norm_stderr": 0.027941727346256308 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3054187192118227, "acc_stderr": 0.032406615658684086, "acc_norm": 0.3054187192118227, "acc_norm_stderr": 0.032406615658684086 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.36363636363636365, "acc_stderr": 0.03756335775187896, "acc_norm": 0.36363636363636365, "acc_norm_stderr": 0.03756335775187896 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4595959595959596, "acc_stderr": 0.035507024651313425, "acc_norm": 0.4595959595959596, "acc_norm_stderr": 0.035507024651313425 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.39378238341968913, "acc_stderr": 0.03526077095548237, "acc_norm": 0.39378238341968913, "acc_norm_stderr": 0.03526077095548237 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.36923076923076925, "acc_stderr": 0.024468615241478905, "acc_norm": 0.36923076923076925, "acc_norm_stderr": 0.024468615241478905 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3074074074074074, "